01253nas a2200109   4500008004100000245007100041210006900112520088200181100002201063700002301085856003501108       2013                        eng d00aMeasuring the Complexity of Ultra-Large-Scale Evolutionary Systems0 aMeasuring the Complexity of UltraLargeScale Evolutionary Systems3 aUltra-large scale (ULS) systems are becoming pervasive. They are inherently complex, which makes their design and control a challenge for traditional methods. Here we propose the design and analysis of ULS systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. We evaluate the proposal with a ULS computing system provided with genetic adaptation mechanisms. We show the evolution of the system with stable and also changing workload, using different fitness functions. When the adaptive plan forces the system to converge to a predefined performance level, the nodes may result in highly unstable configurations, that correspond to a high variance in time of the measured complexity. Conversely, if the adaptive plan is less "aggressive", the system may be more stable, but the optimal performance may not be achieved.1 aAmoretti, Michele1 aGershenson, Carlos  uhttp://arxiv.org/abs/1207.6656